Jianning Yang
Papers
1
Total Citations
8
H-Index
1
About
Jianning Yang is a researcher specializing in robotics, computer vision, and sensor calibration, with a particular focus on uncalibrated robotic systems. Their most-cited work, "Robot-world and hand–eye calibration based on motion tensor with applications in uncalibrated robot" (2022, 8 citations), introduces a novel motion tensor-based approach to solving the simultaneous robot-world and hand-eye calibration problem—a critical challenge for autonomous manipulation and visual servoing. This contribution provides a robust, closed-form solution that eliminates the need for prior calibration, enabling more flexible and accurate robot control in unstructured environments. Yang's research bridges theoretical geometry and practical robotics, offering significant implications for industrial automation and collaborative robots. While still early in their career, their work has already garnered attention for its innovative use of tensor algebra to unify calibration tasks, demonstrating strong potential for future impact. Yang's achievements highlight a promising trajectory in advancing robotic perception and control systems.
Research Focus
Key Achievements
Top Papers
- 1